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Abstract

Background

Demographic ageing is associated with an increasing number of dementia patients, who
reportedly incur higher costs of care than individuals without dementia. Regarding
Germany, evidence on these excess costs is scarce. Adopting a payer perspective, our
study aimed to quantify the additional yearly expenditures per dementia patient for
various health and long-term care services. Additionally, we sought to identify gender-specific
cost patterns and to describe age-dependent cost profiles.

Methods

The analyses used 2006 claims data from the AOK Bavaria Statutory Health Insurance
fund of 9,147 dementia patients and 29,741 age- and gender-matched control subjects.
Cost predictions based on two-part regression models adjusted for age and gender and
excess costs of dementia care refer to the difference in model-estimated means between
both groups. Corresponding analyses were performed stratified for gender. Finally,
a potentially non-linear association between age and costs was investigated within
a generalized additive model.

Results

Yearly spending within the social security system was circa €12,300 per dementia patient
and circa €4,000 per non-demented control subject. About two-thirds of the additional
expenditure for dementia patients occurred in the long-term care sector. Within our
study sample, male and female dementia patients incurred comparable total costs. However,
women accounted for significantly lower health and significantly higher long-term
care expenditures. Long-term care spending increased in older age, whereupon health
care spending decreased. Thus, at more advanced ages, women incurred greater costs
than men of the same age.

Conclusions

Dementia poses a substantial additional burden to the German social security system,
with the long-term care sector being more seriously challenged than the health care
sector. Our results suggest that female dementia patients need to be seen as a key
target group for health services research in an ageing society. It seems clear that
strategies enabling community-based care for this vulnerable population might contribute
to lowering the financial burden caused by dementia. This would allow for the sustaining
of comprehensive dementia care within the social security system.

Keywords:

Background

Dementia disorders are characterized by a progressive loss of cognitive function accompanied
by increasing need for support in daily life. So far, dementia is incurable, and pharmacological
and non-pharmacological interventions can only delay its progression
[1].

Regarding Germany, about 7.2% of the resident population aged 65 and older is estimated
to suffer from dementia
[2,3]. The risk of developing dementia rises in older age
[2,3], and thus the number of patients is expected to double to 2.4 million as a result
of demographic ageing by 2050
[4].

About 85% of Germany’s inhabitants are insured within the social security system,
which is characterized by pay-as-you-go financing, income-dependent but not risk-dependent
insurance contributions and the availability of long-range health and long-term care
services for a small copayment
[5]. In an ageing society, these principles are associated with a widening gap between
receipts and expenditures. Hence, the interest in quantifying the economic burden
of age-associated diseases as dementia grows.

Within the last 15 years, several studies have estimated annual per capita expenditures
of Statutory Health Insurance (hereafter SHI) and Compulsory Long-Term Care Insurance
(hereafter LTCI) on patients with Alzheimer’s dementia. To ensure comparability with
our own data referring to 2006 as the base year, we first converted the reported figures
to Euros by applying the average currency exchange rate of the corresponding year
and, secondly, inflated these figures to 2006 values by applying the German gross
domestic product deflator.

Based on expert interviews, Hallauer and colleagues calculated circa €15,000 (original
value: DM27,500) as the annual cost of care
[6]. By means of patient records, Schulenburg and collaborators estimated a minimum of
€6,600 if all patients had received community-based care from relatives and a maximum
of €12,400 if all patients had received institutional care (original values: $8,100
and $15,200)
[7]. Kiencke et al. presented a claims data-based Markov model, indicating costs of circa
€13,400 per year survived across different pharmacological treatment groups (original
value: €13,100)
[8].

Disregarding a comparison with non-demented control subjects, the cited research left
unclear whether dementia per se is linked to an increase in health and long-term care
expenditures.

International studies suggest that dementia patients incur far higher costs than individuals
without dementia irrespective of the perspective adopted
[9-13]. In the German context, information on these so called excess costs is scarce. We
found one study adopting a societal perspective
[14] and one piece of research adopting the perspective of the social security system
[15].

Standardized for the German resident population aged 60 years and older, the latter
estimated annual per capita expenditures of circa €13,300 (original value: €13,800)
for insurants with a dementia diagnosis compared with circa €3,600 (original value:
€3,700) for insurants without such a diagnosis
[15]. Around 63% of additional costs were attributable to LTCI.

Further evidence is needed regarding the contribution of different health and long-term
care services to the increased spending. Using claims data from a large regional SHI
fund for a case–control comparison, this paper has the threefold objective of:

(1) comparing expenditures for dementia patients and non-demented control subjects
within the distinct service categories of SHI and LTCI;

(2) searching for potential gender differences regarding total costs of care and costs
within the distinct service categories; and

(3) analysing age-dependent cost profiles.

Methods

Data source and sample selection

AOK Bavaria is the leading SHI fund in the district of Middle Franconia covering about
50% of the resident population aged 65 years and older. For 2005–2007, we received
their complete claims data for all insurants in this age group. Data provision was
carried out according to German data protection laws, and AOK Bavaria approved the
use of the data set for the intended analyses.

We restricted our selection process to insurants with records in all three years born
before 1941, leading to a baseline data set of 151,171 individuals. The allocation
to the case and the control group was based on 2005 and 2006 data, and costs were
evaluated for 2006.

We identified people suffering from dementia by constructing ‘dementia quarters’,
based on inpatient diagnoses, outpatient diagnoses and anti-dementia drug prescriptions.
Dementia diagnoses included the ICD-10 codes F00, F01, F02, F03 and G30. Anti-dementia
drug prescriptions consisted of donepezil, galantamine, rivastigmine (all ATC code
‘N06DA’) and memantine (ATC code ‘N06DX01’). In Germany, cholinesterase inhibitors
and memantine are licensed for the treatment of Alzheimer’s dementia only; thus, the
prescription of a corresponding drug was seen as on a par with an explicit diagnosis.
Whenever one of these ICD-10 codes and/or one of these ATC codes was documented at
least once within a quarter, the corresponding quarter was defined as a dementia quarter.

A total of 14,721 insurants showed dementia quarters. To increase the validity of
diagnoses, we excluded 2,136 individuals with their first documented dementia quarter
in IV/2006 and 545 individuals not continuously enrolled in AOK Bavaria. By this method,
12,040 dementia patients remained.

Considering the chronic course of dementia, we required the documentation of at least
three dementia quarters within four consecutive quarters
[16,17] to classify an insurant as an ‘assured dementia case’. At least one of these dementia
quarters had to be in 2006, the year of cost analysis. To avoid loss of information,
we defined all patients with dementia quarters who did not fulfil these two requirements
as ‘potential dementia cases’. This process led to 9,147 patients with assured dementia
(case group) and 2,893 patients with potential dementia. The latter were included
in a sensitivity analysis.

From the remaining subjects without dementia quarters (n = 136,450), we dropped 1,122
individuals with piracetam prescriptions. Treatment with piracetam is common in dementia
disorders, but it is not an exclusively dementia-specific medication. We could not
control for the consumption of ginkgo biloba because SHI reimbursement is limited
for these pharmaceuticals, and therefore they are usually paid out-of-pocket.

Age- and gender-matched control subjects to the assured dementia patients were randomly
selected from the 135,328 potential control subjects in a 4:1 ratio. As the dementia
prevalence in men aged 84 onwards and in women aged 82 onwards exceeded 20%, an exact
4:1 matching was not feasible. For these age groups, we included all remaining potential
control subjects, and the eventual control group contained 29,741 individuals.

The inclusion criteria for our study sample are summarized below:

(1) Aged at least 65 years on 1 January 2006.

(2) Continuously insured with AOK Bavaria in 2005 and 2006.

(3) Case group

(a) At least three dementia quarters within four consecutive quarters of 2005 and
2006

(b) At least one dementia quarter in 2006

(4) Control group

(a) No dementia quarter in 2005 and 2006

(b) No piracetam prescription in 2005 and 2006

Costs of care

The German social security system provides health insurance, long-term care insurance,
pension insurance, (occupational) accident insurance and unemployment insurance. Payments
of the last two benefits are dispensed with on retirement, and the amount of retirement
pay is not affected by health status. Thus, cost differences in the health and long-term
care sector are an acceptable base on which to estimate excess expenditures for dementia
patients within the social security system
[15].

Whenever a treatment took place only partly in 2006, we calculated treatment duration
within the observation period. Then, costs were attributed proportionally to the time
of resource use, implying constant amounts per day.

Physician services are billed via a fee for service system that settles a specific
score for each service. The monetary value of services is calculated by multiplying
this score by a quarter- and specialization-specific point value. We converted the
scores into Euro amounts by applying the corresponding monetary point values published
by the Association of SHI Physicians of Bavaria.

The medication category includes all prescribed drugs. The corresponding pharmacy
retail prices are available from the Scientific Institute of the AOK. However, pharmacies
distribute not only drugs but also to some extent medical aids (e.g. blood pressure
meters, blood glucose meters or bandages), which also occur under the heading medication
because of accounting rules.

The expenditures for non-physician services and home health care reported in the claims
data refer to prescriptions. A prescription for non-physician services covers a fixed
number of treatment sessions, whereas home health care is limited to a distinct time
horizon. The absolute payment amount per prescription depends first on the number
of contacts between patient and provider and second on the type of services provided.
These details on intensity of resource utilization are not traceable; instead, only
the total sum accrued for the delivered services is reported.

Background information on LTCI

Despite being designed as an individual social insurance branch, LTCI is managed under
one umbrella with SHI.

It addresses people with continuous need for support due to physical impairment and
supports various community-based and institutional long-term care services.

The Code of Social Law defines three care levels, each connected to a fixed monthly
tariff for community-living or institutionalized beneficiaries. These payments represent
supplementary financial support and are not intended to provide full coverage of costs
incurred for long-term care. In order to profit from LTCI services, an application
is required followed by an appraisal from the Medical Review Board of the SHI Funds.

To quantify per capita costs within the social security system, we added LTCI and
SHI expenditures and labelled the sum costs of formal care.

Statistical analysis

For a first impression, we compared unadjusted mean per capita expenditures for dementia
patients and non-demented control subjects using Wilcoxon tests, which account for
the highly skewed distribution of cost data.

Our primary analysis adjusted for the covariates age and gender. It applied generalized
linear models (hereafter GLM) assuming a gamma distribution with log link. Cost differences
were evaluated via two different approaches: approach 1 for categories in which costs
were incurred by almost every patient and approach 2 for categories with a user quota
below 90%.

In approach 1, a one-step GLM adjusted for age and gender was performed to estimate
annual per capita expenditures for cases and control subjects. We assigned a small
positive value to the few individuals without costs to avoid their exclusion from
the analyses. Approach 1 was used for the domains general practitioner, medication,
SHI expenditures and costs of formal care.

For the categories medical specialist, hospital treatment, non-physician services,
medical aids, home health care, rehabilitation and long-term care services, we followed
approach 2, in which we calculated two-part regression models
[18]. Part 1 estimated the probability of positive expenditures based on logistic regression.
In part 2, a gamma model, as described above, was applied to estimate the annual amount
of expenditures for those with positive expenditures. Both stages included age and
gender as covariates. To derive per capita costs, the estimated probabilities for
positive expenditures were multiplied by the predicted costs per user. Recycled predictions
with dementia as the coefficient of interest were used to investigate differences
between the case and the control group combined for both stages
[19]. In this approach, two predictions are derived based on the regression estimates:
first, assuming all subjects do not have dementia; second, assuming that all have
dementia. The mean differences between these predictions are the excess costs of dementia
adjusted for covariates
[20].

Adjusted SHI expenditures and adjusted costs of formal care as per the regression
model differed slightly from the sum of adjusted mean costs in the distinct categories,
which results from the stepwise calculation within the two-part model (approach 2).
Moreover, the two-part model provided two p-values, the first referring to differences
in the probability of service use, and the second referring to cost differences among
service users. We assumed a significant difference at the patient level if both parts
pointed in the same direction and if at least one of the two p-values was significant.

We also tested an extended model which considered all possible single interaction
terms between gender, age and dementia. Cost estimations were comparable, but the
interpretation of p-values would have been less straightforward. Thus, we chose the
simple model without interaction terms.

Excess costs of dementia care were obtained by subtracting the estimated costs per
control subject from the estimated costs per case
[21]. For total costs, we calculated the 95% confidence interval of adjusted costs based
on 1,000 nonparametric bootstrap replications.

Supplementary to the primary analysis, we performed two sensitivity analyses. Sensitivity
analysis 1 defined dementia less strictly and included the 2,893 potential cases.
In sensitivity analysis 2, the regression models considered dummy variables for specific
comorbid conditions and death in 2007. We included the five most common comorbidities
from the complex ‘cardiovascular and metabolic disorders’
[22], which were hypertension (ICD I10–I15), lipid metabolism disorder (ICD E78), diabetes
mellitus (ICD E10–E14), chronic ischaemic heart disease (ICD I20, I21, I25) and cardiac
insufficiency (ICD I50). An insurant was considered to suffer from the respective
disease if a corresponding ICD was coded at least once in 2006.

As a secondary analysis, we investigated gender differences regarding costs of care,
within a stratified model. Again, recycled predictions were calculated, this time
with gender as the coefficient of interest. Here, the interaction term ‘dementia*gender’
was also included in the previously described GLMs. Further interactions were disregarded,
which enables an isolated observation of the gender effect in the case and in the
control group.

Within a tertiary analysis, we evaluated a possible non-linear association between
age and costs of formal care, SHI expenditures and LTCI expenditures. We therefore
fitted a generalized additive model allowing a separate smooth function of age for
the four subgroups of male control subjects, female control subjects, male cases and
female cases. The smooth functions were estimated using thin plate regression splines,
and smoothing parameters were estimated using generalized cross-validation
[23].

A significance level of 5% was used for all analyses, which were performed with the
software package SAS, version 9.2.

Results

Baseline characteristics

According to Table
1, dementia patients were around 2 years older than control subjects and had a higher
share of females because of the imperfect matching.

After adjustment for these demographic differences, they still depended to a larger
percentage on professional long-term care and were more likely to die within the year
following the observation.

The potential dementia patients who were disregarded within the matching algorithm
were younger and had a lower female quota than the cases and control subjects. Regarding
the other baseline characteristics, they ranged between both groups with a slight
tendency towards the case group.

Diabetes and heart diseases were more prominent in dementia patients but hypertension
and lipid metabolism disorder in control subjects.

Expenditures within the case and the control group

Costs of care and excess expenditures

The comparison of unadjusted means yielded annual expenditures of circa €12,600 for
dementia patients and circa €4,000 for non-demented control subjects. As highlighted
in Figure
1, costs for dementia patients were increased for all categories except medical specialists.
Apart from rehabilitation, all observed differences were significant.

Figure 1.Unadjusted mean expenditures per year for dementia patients and non-demented control
subjects.

Table
2 summarizes the model-based cost estimates adjusting for age and gender differences
in both groups. In this primary analysis, annual costs of formal care were circa €12,300
in the case group and almost equally distributed between SHI and LTCI. In the control
group, the corresponding ratio was around 80:20, totalling annual expenditures of
circa €4,000.

Table 2.Annual per capita costs (€) and estimated excess costs (€) adjusted for age and gender

Focusing on the distinct categories itemised in Table
2, dementia patients incurred consistently higher spending than control subjects. The
difference was not significant in the use of medical specialists. Total SHI expenditures
were increased by circa 80% and LTCI expenditures by circa 700%. Around two-thirds
of the excess expenditures on formal care were attributable to LTCI.

Table
3 illustrates how differences in per capita expenditures came about: first, except
for rehabilitation, the probability of service use was significantly increased in
dementia patients (p1). Second, the average spending on service users with dementia
was in general remarkably higher than the average spending on service users without
dementia (p2). Regarding medical specialists, the probability of service utilization
and costs per user pointed in opposite directions. This resulted in an insignificant
difference at the per capita level.

Table 3.Probability of service use and annual costs per user adjusted for age and gender

Sensitivity analysis 2, which adjusted for comorbidity, again revealed annual costs
of formal care of circa €12,300 in dementia patients and circa €4,100 (primary analysis:
circa €4,000) in non-demented control subjects. The excess expenditures for dementia
patients were comparable to the primary analysis.

Gender-specific cost profiles

Costs of care and excess expenditures for dementia patients according to gender

Similar to the primary analysis, the gender-stratified GLM revealed significant cost
differences between male cases and male control subjects as well as between female
cases and female control subjects regarding all service categories except medical
specialists (results not shown).

Adjusted for age, annual costs of formal care amounted to circa €12,600 in male dementia
patients and circa €4,300 in male control subjects. The corresponding figures observed
in females were slightly lower with circa €12,200 in dementia patients and circa €3,900
in non-demented control subjects.

Table 4.Gender-specific annual mean expenditures within the case group adjusted for age

Within SHI, spending on home health care and medical aids was remarkably increased
in female dementia patients, but male dementia patients incurred substantially higher
expenditures regarding medical specialists, hospital treatment and non-physician services.
Expenditures for rehabilitation, general practitioners, medication in general as well
as for anti-dementia drugs in particular did not differ.

Within the control group, we also observed increased SHI expenditures in men and increased
LTCI expenditures in women. Here, the comparably low LTCI expenditures failed to balance
spending within both branches, leading to higher costs of formal care for men (results
not shown).

Age-dependent cost profiles

Costs of formal care for dementia patients and control subjects increased with age.
This effect was driven by rising LTCI spending, as SHI expenditures declined concurrently,
as plotted in Figure
2.

Owing to increasing LTCI expenditures, costs of formal care for females exceeded costs
for males at more advanced age, which affected cases about 10 years earlier than control
subjects.

Within both genders, the differences in SHI expenditures, LTCI expenditures and costs
of formal care between dementia patients and non-demented control subjects reduced
slightly in older age.

In general, the impact of age on the three cost outcomes was highly significant (p < 0.0001)
within all four subgroups. The only exceptions were borderline significance regarding
costs of formal care in male dementia patients (p = 0.06) and insignificance regarding
costs per LTCI user in male control subjects (p = 0.99).

These results remained stable when including proximity to death and comorbidity in
the model.

To better understand the interactions between various covariates, we reverted to the
extended model with interaction terms. As documented in Table
5, the age-dependent cost profiles of women progressed more steeply than those of men
(impact of ‘age*female gender’ >1). Moreover, the age-dependent cost trend was less
pronounced within the case group (impact of ‘age*dementia’ <1) but, apart from long-term
care, the dementia diagnosis affected the curves of female patients more severely
than those of male patients (impact of ‘female gender*dementia’ >1).

Discussion

Adopting the perspective of the German social security system, our primary analysis
revealed annual per capita costs for dementia patients of circa €12,300. This is in
good agreement with previous national estimates based on patient-level data
[7,8,15].

Dementia patients were approximately three times more expensive than non-demented
control subjects. They incurred excess costs of around €8,300, about two-thirds of
which occurred in the long-term care sector.

Given a female majority among dementia patients
[2,16], the women’s cost profile influences the cost structure of the entire population.
Within the general older population, previous research observed significantly less
spending on ‘acute medical services’ combined with significantly higher spending on
‘durable supportive services’ in females
[24,25]. The latter is probably because older women are more likely to live alone than men
of the same age and might thus have less access to informal care: older men perhaps
still live with a (slightly younger) spouse who can act as an informal caregiver,
whereas older women are more often widowed. Owing to the longer life expectancy of
females, the living situation described is especially pronounced among the oldest
of the old. Moreover, women were found to develop a comparable level of disability
about 10 years earlier than men
[25], which seems to be a further aspect leading to their increased usage of formal care
services. Our secondary analysis validated this gender-specific cost compilation for
individuals with dementia.

The cost profiles of the tertiary analysis revealed a continuous increase in LTCI
spending accompanied by decreasing SHI expenditures in older age. The increase in
LTCI spending overcompensates for the decline in SHI spending by a long way; thus,
it seems obvious that demographic ageing affects the organization of long-term care
services more seriously than the organization of health care services.

An interesting subsidiary finding of the tertiary analysis was the steadily declining
SHI profile of dementia patients, which contradicted the expected inverse u-shape
[26]. This picture might reflect a reduced ability of individuals with dementia to communicate
their health care needs adequately
[27] or even denote that expensive or interactive treatment strategies are not considered
worthwhile in this population.

We are aware that our results need to be interpreted cautiously because of some methodological
restrictions.

We did not adjust for comorbidity because we assumed a direct connection between dementia
and the occurrence of several comorbid conditions and their respective treatment costs
[11,28,29]. Including comorbidity as an additional confounder might have covered this specific
impact of dementia on existing comorbid conditions. This decision seems not to result
in remarkable bias as the comorbidity-adjusted sensitivity analysis yielded comparable
results.

We also disregarded institutionalization within our regression models to avoid overadjustment
as a dementia diagnosis is a strong predictor for nursing home placement
[30-32]. The overall care strategies probably differ between community setting and institutional
setting, which implies a setting-specific compilation of services.

Moreover, claims data as the single source of information imply specific advantages
and disadvantages
[33].

The accuracy of diagnoses remains uncertain, and the agreement of different data sources
is insufficient regarding dementia disorders
[34-37]. Requiring multiple dementia indicators enhances the validity of case group assignment
but also selects more severe cases, whereas relying on one single indication implies
a higher risk of false-positive classification. We consider our strategy to distinguish
assured and potential dementia patients as a practicable solution, and suppose the
‘true’ excess costs of dementia care to lie in between the results of both analyses
(circa €8,300 vs. circa €7,400). However, our approach regarded a minimum of three
anti-dementia drug prescriptions within four consecutive quarters as on a par with
a minimum of three dementia diagnoses in the corresponding period. By this method,
we included 149 individuals (1.6%) who never received a dementia diagnosis despite
it might have been more precise to assume mild cognitive impairment instead of manifest
dementia in these cases. Given the low percentage, we desisted from excluding the
individuals concerned.

Moreover, claims data lack information on disease severity. Thus, the impact of disease
progression on costs
[38] could not be accounted for despite the cost impact of disease severity is well documented
especially in the field of long-term care
[6,14,39]. Educational level, economic situation and family status are also only traceable
rudimentarily from claims data, but the association between these variables and service
utilization is broadly accepted. For example, living alone is a predictor for long-term
care expenditures, because single people are presumed to have less access to informal
support and therefore assumed to rely to a larger extent on professional help
[40].

On the other hand, relying on claims data prevents the disregarding of considerable
parts of the effective patient clientele. Observational studies and clinical trials
based on primary information often do not address frail and institutionalized individuals.
In contrast, claims data account for all insurants irrespective of health status and
living environment and are thus less selective.

To ensure sound decision making, unambiguous economic information for the payer is
paramount. Cost information from claims data are basically reliable, because they
report the de facto spending on a broad range of medical and non-medical services.
Thus, defining unit costs and extrapolating self-reported data becomes dispensable.
The accuracy of such estimates is unclear, because assuming the recall period to be
representative of the entire observation period seems questionable, and self-reported
service utilization may be impaired by recall bias
[41].

Regarding the future organization of dementia care, it must not be forgotten that,
despite not being accounted for within a payer perspective, informal care is the crucial
expense factor
[14,39,42], especially in the community setting. The number of potential family caregivers will
decrease because of changing living arrangements, increasing women in the labour force
and decreasing birth rates in industrialized countries. Thus, a shift from informal
towards formal care and a rising economic burden for social security systems can be
expected all round the world. Our data provide information on the age- and gender-specific
health and long-term care needs of individuals with dementia. This knowledge is a
suitable starting point for developing targeted programmes to manage future care for
this clientele efficiently.

Conclusions

Our data suggest a special need to regard female dementia patients as a crucial target
group. Owing to longer life expectancy, women face an increased risk of developing
dementia. Moreover, females rely earlier and to a larger extent on professional long-term
care than males. Dementia leads in turn to a comparatively early dependency on long-term
care services. These services are the crucial expense factor in dementia care, and
the corresponding expenditures rise steeply with age. Altogether, innovative strategies
fostering community-based long-term care for females with dementia can influence the
key driver of the financial burden resulting from dementia disorders. This would help
to sustain a socially acceptable financing of comprehensive dementia care within the
social security system.

Competing interests

For LS, PMe, RL, RH (Helmholtz Zentrum München), and EG (University Hospital Erlangen
- Clinic for Psychiatry and Psychotherapy) their institution received support from
the funding organisations for the submitted work. SW (AOK Bavaria), HM (Eisai GmbH)
and PMa (Pfizer Deutschland GmbH), are employees of one of the funding organisations
and received a regular salary while contributing to the work; RL and EG received a
honorarium from one of the funding organizations for presenting data or participating
in an advisory board.

Authors’ contributions

LS analysed the data and wrote the manuscript. PMe developed the statistical models
and revised the statistics section of the manuscript. Together with RH, both decided
on study design and the research questions to be answered. RL, SW, HM, PMa and EG
advised on health care system-related issues and were involved in the constitution
of the final study design. All authors contributed to the manuscript and approved
the final version of the manuscript. RH is guarantor.

Acknowledgements

The authors thank Simone Kunz who suggested evaluating the excess costs of dementia
care and thus gave the initial impulses for conducting our study. We also acknowledge
the continuous support of Andrea Wulff and Harald Hänsch who prepared the database
and substantial parts of the SAS programs for our analyses. Moreover, we are grateful
for the inputs of the referees whose comments and suggestions significantly improved
both the clarity and the precision of the article.

Funding

The study on ‘excess costs of dementia’ is an add-on to the IDA project, which was
initiated and financed by the Federal Association of the AOK, the AOK Bavaria - Health
Insurer and the research-based pharmaceutical companies Eisai and Pfizer. The sponsors
have commissioned the Helmholtz Zentrum München - Institute of Health Economics with
the scientific evaluation of the claims data by giving unconditional research funds.
A contract between the sponsors and academic researchers ensures that the latter have
full scientific responsibility and the right to publish the results.

References

Dementia Guideline Development Group: Dementia - The NICE-Scie Guideline on supporting people with dementia and their carers
in health and social care. London: The British Psychological Society, The Royal College of Psychiatrists; 2007.